Uncertainty: Difference between revisions
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<onlyinclude>'''Uncertainty''' is an expression of the degree to which a value or relationship is unknown.</onlyinclude> It is often expressed by a range of values | [[File:Ggplot2-barplot-with-error-bar-data-visualization-1.png|thumb|Figure 1. A graph with error bars to express uncertainty in data.<ref>STHDA (2021). (Accessed June 11, 2026). ''ggplot2 barplots : Quick start guide - R software and data visualization'' [Online]. Available: https://www.sthda.com/english/wiki/ggplot2-barplots-quick-start-guide-r-software-and-data-visualization</ref>]] | ||
<onlyinclude>'''Uncertainty''' is an expression of the degree to which a value or relationship is unknown.</onlyinclude> It is often expressed by a range of values written as: "'''x ± y'''" with '''x''' being the ''recorded value'', and '''y''' being its ''uncertainty''. This means that the value that was measured is ''not'' ''exactly'' '''x''', but lies in a range '''± y''' from '''x'''. Uncertainty can result from lack of information or from disagreement about what is known or even knowable. Due to deep ideas in physics, measurements cannot be made to arbitrary accuracy; all measurements must carry with them an uncertainty, often made as an educated guess. | |||
For example, if measuring the height of a building, one could use a high precision instrument to record the building being 30.00 ± 0.01 [[meter]]s, or more primitive techniques yielding a result of 28 ± 5 meters. Both methods give a range of uncertainty, regardless of the precision of the instrument; high precision just means that this range is much smaller. | |||
Uncertainty may originate from many sources, such as quantifiable errors in the data, ambiguously defined concepts or terminology, or uncertain projections of human behavior. Uncertainty can therefore be represented by quantitative measures, for example, a range of values calculated by various models, or by qualitative statements, for example, reflecting the judgment of a team of experts.<ref name="IPCC_SREX">IPCC, 2012: Glossary of terms. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, Cambridge, UK, and New York, NY, USA, pp. 555-564.</ref> Figure 1 is a graph featuring error bars, which visually represent uncertainty. | |||
Uncertainty may originate from many sources, such as quantifiable errors in the data, ambiguously defined concepts or terminology, or uncertain projections of human behavior. Uncertainty can therefore be represented by quantitative measures, for example, a range of values calculated by various models, or by qualitative statements, for example, reflecting the judgment of a team of experts.<ref name=IPCC_SREX>IPCC, 2012: Glossary of terms. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, Cambridge, UK, and New York, NY, USA, pp. 555-564.</ref> | |||
''For the Uncertainty Principle in Quantum Mechanics, please visit [http://hyperphysics.phy-astr.gsu.edu/hbase/uncer.html HyperPhysics].'' | ''For the Uncertainty Principle in Quantum Mechanics, please visit [http://hyperphysics.phy-astr.gsu.edu/hbase/uncer.html HyperPhysics].'' | ||
== | ==For Further Reading== | ||
*[[Likelihood]] | *[[Likelihood]] | ||
*[[Confidence]] | *[[Confidence]] | ||
*[[Predictability]] | |||
*Or explore a [[Special:Random|random page]] | |||
==References== | ==References== | ||
{{reflist}} | {{reflist}} | ||
[[Category: Uploaded]] | |||
Latest revision as of 20:55, 2 July 2026
Uncertainty is an expression of the degree to which a value or relationship is unknown. It is often expressed by a range of values written as: "x ± y" with x being the recorded value, and y being its uncertainty. This means that the value that was measured is not exactly x, but lies in a range ± y from x. Uncertainty can result from lack of information or from disagreement about what is known or even knowable. Due to deep ideas in physics, measurements cannot be made to arbitrary accuracy; all measurements must carry with them an uncertainty, often made as an educated guess. For example, if measuring the height of a building, one could use a high precision instrument to record the building being 30.00 ± 0.01 meters, or more primitive techniques yielding a result of 28 ± 5 meters. Both methods give a range of uncertainty, regardless of the precision of the instrument; high precision just means that this range is much smaller.
Uncertainty may originate from many sources, such as quantifiable errors in the data, ambiguously defined concepts or terminology, or uncertain projections of human behavior. Uncertainty can therefore be represented by quantitative measures, for example, a range of values calculated by various models, or by qualitative statements, for example, reflecting the judgment of a team of experts.[2] Figure 1 is a graph featuring error bars, which visually represent uncertainty.
For the Uncertainty Principle in Quantum Mechanics, please visit HyperPhysics.
For Further Reading
- Likelihood
- Confidence
- Predictability
- Or explore a random page
References
- ↑ STHDA (2021). (Accessed June 11, 2026). ggplot2 barplots : Quick start guide - R software and data visualization [Online]. Available: https://www.sthda.com/english/wiki/ggplot2-barplots-quick-start-guide-r-software-and-data-visualization
- ↑ IPCC, 2012: Glossary of terms. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, Cambridge, UK, and New York, NY, USA, pp. 555-564.